How Finch is scaling plaintiff law with AI agents that research like associates

Finch, a company that aids plaintiff law firms by pairing AI agents with an in-house legal team to streamline research and administrative tasks, has significantly improved its operational efficiency and cost-effectiveness by migrating to Parallel's Task API for web research. This transition has led to a 90% reduction in per-task costs, eliminating previous issues of unreliable API contracts and excessive engineering overhead required for defensive validation. Finch now benefits from structured outputs in a single call, enhancing the quality and scalability of its legal research workflows. The migration has also resulted in zero 5xx errors or timeouts over several months in production, allowing the engineering team to focus on product development rather than API maintenance. Finch's use of Parallel's tiered pricing model enables them to align computing resources with the complexity of individual queries, optimizing both cost and performance.

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